Sensitivity Analyses of Four Systemic Lupus Erythematosus Disease Activity Indices in Predicting the Treatment Changes in Consecutive Visits: A Longitudinal Study Publisher Pubmed



Fatemi A¹ ; Raeisi A² ; Sayedbonakdar Z¹ ; Smiley A³ Show Affiliations
Source: Clinical Rheumatology Published:2018

Abstract

This study was conducted to assess the ability of the British Isles Lupus Assessment Group-2004 (BILAG-2004), the SLE Disease Activity Index-2K (SLEDAI-2K), the European Consensus Lupus Activity Measurement (ECLAM), and the Revised Systemic Lupus Activity Measure (SLAM-R) to detect the need to treatment change in daily clinical practice. One hundred and two patients with SLE were enrolled and followed up for 2 to 8 months and visited at least 3 times. Physician Global Assessment, BILAG-2004, SLEDAI-2K, SLAM-R, and ECLAM, were calculated in every visit. Treatment change, dependent variable, was categorized as decrease/no change vs. increase. The aforementioned indices, independent variables, were compared to learn their ability in predicting the treatment change. The probability of treatment change was measured by generalized linear-mixed effect model (GLMM) and generalized estimating equations (GEE). Adjusted odds ratios were calculated. Predictive power of indices was compared by area under the curve (AUC) in plots of sensitivity vs. 1-specificity and application of receiver operating characteristic curves (ROC). BILAG-2004 and SLEDAI-2K had substantial correlation with treatment change. Among different GLMM models, BILAG-2004 followed by SLEDAI-2K showed the highest associations with treatment change. Among various GEE models, similar findings were observed. Also, these 2 indices had the highest sensitivity (the largest AUC) towards treatment change; BILAG-2004 (AUC = 0.779, 95% CI = 0.710–0.848, p = 0.001) and SLEDAI-2K (AUC = 0.771, 95% CI = 0.698–0.843, p = 0.001). BILAG-2004 followed by SLEDAI-2K had the highest predictability of treatment change. © 2017, International League of Associations for Rheumatology (ILAR).